Bonds

Bonds have two price components, yield and response of price to prevailing interest rates. How much of a return premium should investors in bonds expect? How can investors enhance this premium? These blog entries examine investing in bonds.

“Simple Asset Class ETF Value Strategy” finds that investors may be able to exploit relative valuation of the term risk premium, the credit (default) risk premium and the equity risk premium via exchange-traded funds (ETF). However, the backtesting period is limited by available histories for ETFs and for the series used to estimate risk premiums. To construct a longer test, we make the following substitutions for potential holdings (selected for length of available samples):

We retain quarterly average yields for Moody’s Seasoned Baa Corporate Bonds for calculation of the credit risk premium. As with ETFs, we consider two alternative strategies for exploiting premium undervaluation: Best Value, which picks the most undervalued premium; and, Weighted, which weights all undervalued premiums according to degree of undervaluation. Based on the assets considered, the principal benchmark is a quarterly rebalanced portfolio of 60% stocks and 40% U.S. Treasuries (60-40 VWUSX-VFIIX). Using quarterly risk premium calculation data during January 1934 through December 2014 (limited by availability of Moody’s Baa data), and quarterly dividend-adjusted closing prices for the three asset class mutual funds during June 1980 through December 2014 (139 quarters), we find that:

This set of ETFs relates to three factor risk premiums: (1) the difference in yields between Treasury bills and Treasury note/bonds indicates the term risk premium; (2) the difference in yields between corporate bonds and Treasury notes/bonds indicates the credit (default) risk premium; and, (3) the difference in yields between equities and Treasury notes/bonds indicates the equity risk premium. We consider two alternative strategies for exploiting premium undervaluation: Best Value, which picks the most undervalued premium; and, Weighted, which weights all undervalued premiums according to degree of undervaluation. Based on the assets considered, the principal benchmark is a quarterly rebalanced portfolio of 60% stocks and 40% U.S. Treasury notes (60-40 SPY-IEF). Using quarterly S&P 500 Index levels and earnings, quarterly average yields for 3-month Constant Maturity U.S. Treasury bills (T-bills), quarterly average yields for 10-year Constant Maturity U.S. Treasury notes (T-notes), quarterly average yields for Moody’s Seasoned Baa Corporate Bonds during March 1989 through December 2014 (limited by availability of earnings data), and quarterly dividend-adjusted closing prices for the above three asset class ETFs during September 2002 through December 2014 (45 quarters, limited by availability of IEF and LQD), we find that:Keep Reading

Does fourth quarter global economic data set the stage for asset class returns the next year? In their February 2015 paper entitled “The End-of-the-year Effect: Global Economic Growth and Expected Returns Around the World”, Stig Møller and Jesper Rangvid examine relationships between level of global economic growth and future asset class returns, focusing on growth at the end of the year. Their principle measure of global economic growth is the equally weighted average of quarterly OECD industrial production growth in 12 developed countries. They perform in-sample tests 30 countries and out-of-sample tests for these same 12 countries (for which more data are available). Out-of-sample tests: (1) generate initial parameters from 1970 through 1989 data for testing during 1990 through 2013 period; and, (2) insert a three-month delay between economic growth data and subsequent return calculations to account for publication lag. Using global industrial production growth as specified, annual total returns for 30 country, two regional and world stock indexes, currency spot and one-year forward exchange rates relative to the U.S. dollar, spot prices on 19 commodities, total annual returns for a global government bond index and a U.S. corporate bond index, and country inflation rates as available during 1970 through 2013, they find that:Keep Reading

Is the reward for holding risky bonds material and distinct from the reward for holding stocks and the reward for holding longer term bonds? In their February 2015 paper entitled “Credit Risk Premium: Its Existence and Implications for Asset Allocation”, Attakrit Asvanunt and Scott Richardson measure and explore the predictability and diversification power of the credit (or default) risk premium associated with corporate bonds. They focus on the premium associated with creditworthiness of bonds by first removing the influence of duration/interest rates. They also test whether the credit risk premium diversifies the equity risk premium and the bond term premium. Using data for U.S. corporate bonds, the U.S. stock market, U.S. Treasury securities and economic indicators during 1927 through 2014 and for credit default swaps (CDS) during 2004 through 2014, they find that:Keep Reading

A subscriber requested corroboration of the findings in “Simple Debt Class Mutual Fund Momentum Strategy” with a universe restricted to a family of bond funds (such as Fidelity) to enable low-cost fund switching. We therefore apply the strategy to the following ten Fidelity mutual funds:

Per the prior test, we allocate all funds at the end of each month to the fund with the highest total return over the past three months (3-1). We determine the first winner in May 1994 to accommodate momentum measurement interval sensitivity testing. Using monthly dividend-adjusted closing prices for the ten funds during May 1993 (as limited by FNMIX) through January 2015 (261 months), we find that:Keep Reading

Does optimal asset allocation, as measured by Sharpe ratio, depend on investment horizon? In their January 2015 paper entitled “Optimal Asset Allocation Across Investment Horizons”, Ronald Best, Charles Hodges and James Yoder explore the optimal (highest Sharpe ratio) mix of long-term U.S. corporate bonds and large-capitalization U.S. common stocks across investment horizons from one to 25 years. They test portfolios ranging from 100%-0% to 0%-100% stocks-bonds in 5% increments with annual rebalancing. They estimate annual returns for stocks and bonds based on 87 years of historical data. They simulate the portfolio return distribution for a given n-year holding period via 2,500 iterations for each of two methods:

Randomly select with replacement n years from the 87 years in the historical sample and use the annual returns for U.S. Treasury bills (T-bills, the risk-free rate), stocks and bonds for those n years in the order selected to calculate portfolio gross compound n-year excess returns. This method assumes year-to-year independence (zero autocorrelations) of annual returns for stocks and bonds, meaning no momentum or reversion.

Randomly select a year from the first 87 – (n-1) years in the historical sample and use the annual returns for T-bills, stocks and bonds for that and the next n-1 consecutive years to calculate portfolio gross compound n-year excess returns. This method preserves historical autocorrelations in return series.

What is the best mix of stocks and bonds to hold during retirement worldwide? In his January 2015 paper entitled “The Retirement Glidepath: An International Perspective”, Javier Estrada compares outcomes for different stocks-bonds allocation strategies during retirement from a global perspective. He considers declining equity, rising equity and static glidepaths with an annual withdrawal rate of 4% (of the portfolio value at retirement) and annual rebalancing during a 30-year retirement period. He tests the following glidepaths:

He focuses on the failure rate of these strategies during 81 overlapping 30-year retirement periods during 1900-2009. He also considers average and median terminal wealth/bequest, tail risk, annual volatility (standard deviation of annual returns) and upside potential. He defines tail risk (downside risk) as average terminal wealth for the 1%, 5% or 10% lowest values from the 81 periods. Using annual total real returns for stocks and government bonds for 19 countries (in local currency adjusted by local inflation) and for the world market (in dollars adjusted by U.S. inflation) during 1900 through 2009 (110 years), he finds that:Keep Reading

To investigate, we compare 21 variations of the strategy based on shifting the monthly return calculation cycle relative to trading days from the end of the month (EOM). For example, an EOM+5 cycle ranks funds based on closing prices five trading days after EOM each month. We use the historically optimal two-month fund momentum measurement interval. Using daily dividend-adjusted closes for the 12 funds during mid-December 1994 through mid-January 2015 (241 months), we find that:Keep Reading

A subscriber requested confirmation of the performance of a simple momentum strategy that each month selects the best performing debt mutual fund based on total return over the past three months. To investigate, we test a simple strategy on the following 12 mutual funds (those with the longest histories from a proposed list of 14 funds):

As proposed, we allocate all funds at the end of each month to the fund with the highest total return over the past three months (3-1). We determine the first winner in February 1995 to accommodate momentum measurement interval sensitivity testing. Using monthly dividend-adjusted closing prices for the 12 funds during February 1994 (as limited by VBLTX) through December 2014 (251 months), we find that:Keep Reading